Xiao Jin

and 5 more

Yujie Li

and 4 more

Wildfires have a great impact on the global ecosystem and human society, so the prediction and prevention of wildfires is necessary. This article uses the MOD14A2 data, the NCEP/NCAR and ERA5 Reanalysis data, the GFEDv4 data and the Scripps O2 data to analyze the correlation between wildfires, meteorological elements and oxygen concentration in the Boreal North America (BONA), the Temperate North America (TENA), the Australia and New Zealand (AUST). The following preliminary conclusions were obtained: 1) From 2001 to 2015, 2002 was the year with the most wildfires, and august was the month with the most wildfires. Besides, Northern Africa, Southern Africa and South America are the main wildfires-affected areas, the total wildfires area from 2001 to 2015 is about 2148 million ha, accounting for nearly 80% of the global wildfires area in these 15 years. 2) Globally, the correlation coefficient between temperature and wildfires area is 0.47, between wind speed and wildfires area is 0.17, between precipitation and wildfires area is -0.41; between relative humidity and wildfires area is -0.19. 3) AS the direct path coefficients of oxygen concentration are nearly 0.38, oxygen can be regarded as a variable independent of meteorological elements. In BONA, from 2001 to 2015, the correlation coefficient between oxygen concentration and wildfires area is 0.61; In TENA, the correlation coefficient is 0.62; In AUST, the correlation coefficient is 0.6. This study illustrates the importance of oxygen concentration for wildfires. So, it is of great significance to the prediction and prevention of global wildfires.

Yujie Li

and 4 more

The thermal properties of soil play important roles in biogeochemical cycles. The soil thermal diffusivity can accurately reflect the transient process of soil heat conduction. In this study, we use observation data from the 5, 10, 20, 40, and 80 cm layers in Golmud from October 2012 to July 2013 and comprehensively compare the solution of soil thermal diffusivity thereafter. A new model is established using the thermal conduction-convection equation under Fourier boundary conditions. The results show that (1) the amplitude method and the phase method are based on a single temperature sine wave, which is used to describe the general soil, although the accuracy is not high enough; the logarithmic method and the arctangent method are performed four times a day, the accuracy of the obtained result is also low; moreover, the Laplace method does not have a clear soil temperature boundary function and thus can better address extreme weather effects or nonperiodic changes in soil temperature. (2) When solving the thermal conduction equation by a numerical method, format 2 (Crank-Nichalson-Sch format) is unconditionally stable, the data utilization is higher; in addition, the obtained soil thermal diffusivity is less discrete, and the result is more accurate. (3) When the soil temperature is simulated by the Fourier series, as the order n becomes larger, the result becomes more accurate. The Fourier series performs well in simulating the soil thermal properties. This study provides a useful tool for calculating soil thermal diffusivity, which may help to further characterize biogeochemical cycles.